Alzheimer?s disease (AD), the most common form of dementia, affects over five million people in the United States. A vast majority of cases are the result of late-onset AD (LOAD), which has a wide variability in onset, progression, and severity across the population. We posit that normal aging and AD memory decline result from common molecular pathways; therefore, we expect that the identification of genetic factors and mechanisms underlying normal aging will provide feasible targets for intervention against AD. The identification of genetic risk factors and mechanisms in humans has been impeded largely by the known heterogeneity of degenerative changes, the numerous environmental confounds that can exist in human cohorts, and the difficulty in obtaining molecular and functional data from humans at the preclinical and/or early stages of disease. Genetic reference panels, such as the BXD panel of mice, model a portion of the genetic complexity of human populations while controlling for environmental factors. We will use the BXD panel in order to identify genetic factors and mechanisms that modify the onset and severity of memory decline. We will measure memory function in our BXD panel across their lifespan (6, 12, and 18 mo) and perform subsequent genetic linkage mapping in order to identify genomic areas that correlate to disease progression. We hypothesize that multiple gene variants modulating memory decline do so by altering expression of hippocampal proteins necessary for memory, so we will also quantitatively evaluate protein levels in the hippocampus across the lifespan in BXD strains that exhibit extreme variation in cognitive decline (i.e. susceptible and resilient strains; bottom and top 10%). Candidate risk and protective factors will be selected for functional validation in normal aging and AD mouse models using sequence data, existing hippocampal mRNA from age-matched strains, and numerous bioinformatics resources. Pilot studies suggest candidates involved in expression of hippocampus membrane proteins that modulate neuronal excitability (e.g. Hp1bp3, Trpc3) contribute to individual differences in cognitive aging, and may also impact the development and progression of AD. Thus, up to 5 novel candidate genes (alongside Hp1bp3, Trpc3) will be tested by manipulating gene sequence or expression using viral delivery of genome editing constructs or siRNA, respectively, and measuring the effect on cognitive decline, neurophysiological changes and neuropathological markers of AD using established AD- related mouse models and age-matched controls. The identification of novel genetic factors and mechanisms of memory decline will be a critical first step toward the development of both mechanistic-based treatments and personalized gene therapies that would maintain cognitive function in elderly humans. The identification of predictive genetic variants or neurophysiological biomarkers would also have the tremendous potential to provide biomarkers for earlier detection and more effective treatment in AD patients.